I encountered a strange result in a SEM model. I have 5 latent variables in total. Two latent variables ("racism" and "self-stigma") are not correlated in the measurement model. But in the structural model, "racism" significantly predicted "self-stigma" in negative direction (opposite to what would be expected).

My question is: How can two latent variables be unrelated, but then have a significant path coefficient between them in a structural model?